Seasonal Rainfall Research Articles

Reducing Yearly Variation In Potato Tuber Yield Using Supplemental Irrigation

This study investigated the influence of supplemental irrigation (SI) on yearly variation in potato yield and associated economics in a humid climate. On-farm trials were conducted in four to five fields annually in Prince Edward Island, Canada from 2019 to 2022. The research involved four different treatments: rainfed production as the control group, irrigation following conventional practices, irrigation guided by soil moisture monitoring, and irrigation guided by soil moisture monitoring coupled with a 20% reduction in fertilizer input. While six commonly-grown russet potato cultivars were used, local standard cultural practices were followed at all sites. In 2019 SI significantly increased marketable yields (MY), which was primarily attributed to a drought period that extended from July to early August. Similarly, in 2020 SI led to a substantial rise in MY due to growing season rainfall being significantly lower than the optimal water demand for the potato plant. Conversely, in 2021 and 2022, when rainfall was relatively sufficient and evenly distributed, farmers either refrained from irrigating or employed minimal irrigation rates, resulting in negligible MY responses. Tuber yield increase as a result of SI varied with rainfall and thus fluctuated yearly. Cross-year comparisons revealed that SI can effectively mitigate annual fluctuations in tuber yield. A cost–benefit analysis indicated that employing SI to minimize yearly variation in tuber yield can be either profitable or unprofitable in the long term, and is contingent on the costs linked to irrigation equipment, the water supply system, operational aspects, field scale, and rainfall distribution. These findings hold significance for guiding decisions in water management for potato production in humid environments.

The implication of spatiotemporal rainfall distribution on the estimation of areal rainfall characteristics in Upper Erer Sub-basin, Ethiopia

Abstract The distribution of rainfall is not uniform in various regions of the world. Rainfall study is used to recognize the characteristics, duration, and variability of temporal and spatial rainfall distributions. In Ethiopia, the annual and seasonal rainfall distributions are variable in space and time. This study is focused on the implication of spatiotemporal rainfall distribution on the areal rainfall characteristics evaluation under the Upper Erer Sub-basin, located in Eastern Ethiopia. In the study area, average annual rainfall amount for Dire Dawa, Harar and Haramaya, Girawa, and Gursum stations are found to be 647, 816, 801, 958, and 840 mm with coefficients of variation of 23, 20, 20, 19, and 31%, respectively. However, the rain gauges here are sparsely distributed. The rainfall occurrence and distribution at various gauging stations have been found to vary significantly both temporally and spatially. The rainfall occurrence and distribution at various gauging stations had been found to vary significantly both temporally and spatially. The spatiotemporal rainfall distribution found in the stations was assessed using a joint probability of rain days approach. The result indicated joint probability of rain days estimation approach under monthly time step has better performance than daily, decadal, and seasonal data. The joint probability approach is used along with rainfall amount under monthly rainfall for areal rainfall estimation assessment in rainfall–runoff modeling.

A novel approach to predictor selection among large-scale climate indices for seasonal rainfall forecasting in small catchments

ABSTRACT Utilizing identical climate indices as predictors for all climate divisions within large basins may result in unreliable rainfall forecasts at the sub-basin scale. This study aimed to develop a new approach to identify the most effective predictors among large-scale climate indices for seasonal rainfall forecasting in small areas. The proposed approach combines a selective singular value decomposition method (SSVD) with a non-linear sequential forward selection method (NLSFS). Applying the new algorithm for seasonal rainfall forecasting within two climate divisions in Karkheh basin, Iran, indicated that the climate indices identified by the SSVD differed between the study areas. The combination of these indices exhibited a correlation with seasonal rainfall approximately 11% higher than those derived from the SVD method. Moreover, NLSFS significantly enhanced the forecast accuracy compared to the frequently employed linear sequential forward selection (SFS) method, and the optimal predictors chosen by the two methods differed across all seasons.

Agricultural Practices to Improve Irrigation Sustainability

Water is the main limiting factor in agricultural production in regions where the annual or seasonal rainfall is insufficient for the water requirements of crops [...]

Evaluating the relationship of vegetation dynamics with rainfall and land surface temperature using geospatial techniques in South Wollo zone, Ethiopia

This study was conducted in the South Wollo zone to assess vegetation dynamics and their relationship with rainfall and land surface temperature. To that end, 16-day 250-meter resolution Moderate Imaging Spectro-radiometer (MODIS) Normalized difference vegetation Index (NDVI), 5-kilometer resolution MODIS Land Surface Temperature (LST), 5-kilometer CHIRPS data were used. A Mann-Kendall (MK) trend test was used to determine the trend of each dataset using seasonal and annual time series. In addition, the Pearson correlation coefficient was used to estimate the relationship between NDVI and climatic elements. The results of the study revealed that there was no significant change in the annual and seasonal rainfall and LST during the period 2000 to 2021, except LST in the autumn season (p = 0.01) and NDVI was significant only in the mean annual (p = 0.027) and summer seasons (p = 0.03). The correlation between NDVI and rainfall was positive (r = 0.84, 0.78, 0.72 & 0.79) and obtained for the summer, autumn, winter, and spring season respectively. Similarly, the correlation between NDVI and LST was negative (r= -0.79, -0.75, -0.72, and -0.78) in the summer, autumn, winter, and spring seasons respectively. The outcome of the study indicates precipitation is the most significant factor in the distribution of vegetation and LST

A Pre‐Monsoon Signal of False Alarms of Indian Monsoon Droughts

AbstractCurrent knowledge suggests a drought Indian monsoon (perhaps a severe one) when the El Nino Southern Oscillation and Pacific Decadal Oscillation each exhibit positive phases (a joint positive phase). For the monsoons, which are exceptions in this regard, we found northeast India often gets excess pre‐monsoon rainfall. Further investigation reveals that this excess pre‐monsoon rainfall is produced by the interaction of the large‐scale circulation associated with the joint phase with the mountains in northeast India. We posit that a warmer troposphere, a consequence of excess rainfall over northeast India, drives a stronger monsoon circulation and enhances monsoon rainfall over central India. Hence, we argue that pre‐monsoon rainfall over northeast India can be used for seasonal monsoon rainfall prediction over central India. Most importantly, its predictive value is at its peak when the Pacific Ocean exhibits a joint positive phase and the threat of extreme drought monsoon looms over India.

Australia's Tinderbox Drought: An extreme natural event likely worsened by human-caused climate change.

We examine the characteristics and causes of southeast Australia's Tinderbox Drought (2017 to 2019) that preceded the Black Summer fire disaster. The Tinderbox Drought was characterized by cool season rainfall deficits of around -50% in three consecutive years, which was exceptionally unlikely in the context of natural variability alone. The precipitation deficits were initiated and sustained by an anomalous atmospheric circulation that diverted oceanic moisture away from the region, despite traditional indicators of drought risk in southeast Australia generally being in neutral states. Moisture deficits were intensified by unusually high temperatures, high vapor pressure deficits, and sustained reductions in terrestrial water availability. Anthropogenic forcing intensified the rainfall deficits of the Tinderbox Drought by around 18% with an interquartile range of 34.9 to -13.3% highlighting the considerable uncertainty in attributing droughts of this kind to human activity. Skillful predictability of this drought was possible by incorporating multiple remote and local predictors through machine learning, providing prospects for improving forecasting of droughts.

Climate, agroecology, and farm returns: differential impacts with implications for agricultural progress in the face of climate change

Climate change is expected to have differential impacts on different zones. In this study, we employed the Ricardian technique, estimated through ordinary least squares (OLS) to assess the impact of climate change on farmers’ revenue. We use survey data from two distinct agroecological zones in Cameroon. Our results show that rainfall is the main climatic variable affecting farmers’ revenue. The results are statistically different for the two agroecological zones. While rainfall in the dry season affects revenue in the western highland zone. No climatic variable seems to affect farm revenue in the bimodal forest zone. These results suggest that the abundance of forest in the bimodal zone maybe be shielding the zone from the effects of climate change. We therefore recommend that farmers employ water harvesting and low-cost irrigation methods to cope with changes in rainfall pattern especially in extended dry seasons. Facilitating farmers’ access to climate information particularly with respect to the onset and cessation of rains will improve the planning of farm operations.

Hydrological investigation of climate change impact on water balance components in the agricultural terraced watersheds of Yemeni highland

Hydrological models serve as valuable instruments for assessing the impact of climate change on water resources and agriculture as well as for developing adaptation measures. In Yemen, climate change and variability are imposing a significant impact on the most important sectors such as agriculture and economy. The current study evaluates the influence of future climate on hydrology and water balance components in Yemen’s highlands using a semi-distributed physical-based hydrologic model Soil Water Assessment Tool (SWAT) and employing high-resolution climate projections. The SWAT was calibrated and verified using observed streamflow data from 1982 to 2000 in three large catchments. Ground data from 24 stations and statistically downscaled future climate data for the period 2010–2100 under RCP2.6 and RCP8.5 are used. SWAT performance was assessed using multiple statistical methods, which revealed the commendable performance of SWAT during the calibration (average NSE = 0.80) and validation (NSE = 0.72) periods. The outcome indicates an increase in future seasonal and annual rainfall, maximum temperature, and minimum temperature in the 2020s and the 2080s under both RCP2.6 and RCP8.5 scenarios. This projected increase in the rainfall and the local temperature will result in increased averages of surface runoff, evapotranspiration, soil water, and groundwater recharge in the representative three catchments up to 6.5%, 21.1%, 7.6%, and 6.4%, respectively. Although, the projected increase in the water balance components will benefit the agriculture and water sector, specific adaptation measures will be crucial to mitigate potential flood impacts arising from the increased precipitations as well as to minimize the consequences of the increased temperature. Likewise, demand for supplementary irrigation is expected to increase to offset the higher evapotranspiration rates in the future.

Nitrogen and phosphorus availability alters tree‐grass competition intensity in savannas

Abstract Plant essential macronutrients like nitrogen (N) and phosphorus (P) can limit savanna tree growth and are important determinants of savanna vegetation dynamics, along with rainfall, fire and herbivory. How nitrogen and phosphorus shape tree‐grass competition and their coexistence remain unclear, hindering our ability to predict how savannas may respond to altered nutrient cycling. Here, we evaluate (1) if trees and grasses respond differently to N versus P availability, or (2) if grasses are more competitive in low nutrient environments while trees are more competitive in high nutrient environments. To do this, we grew saplings of 6 tree and 1 grass species from the Kruger National Park, South Africa, for 16 weeks under fully factorial nutrient and competition treatments (with/without competitors, low/high rate of N supply and low/high rate of P supply) under a watering regime designed to mimic wet season rainfall in a mesic savanna. Trees and grasses foraged most aggressively for nitrogen and allocated biomass differently depending on nitrogen availability. Overall, tree growth decreased in competition with grass, even in high nutrient environments where they grew faster. Grasses were always better below‐ground competitors, utilising aggressive nutrient foraging strategies, including high root phosphatase activity in response to nitrogen and large root biomass allocation. Synthesis. In low nutrient environments (e.g. on nutrient‐poor sandy soils), nutrients may limit tree growth. Nutrient rich environments enable tree growth, but grasses continue to compete effectively with trees. Understanding what this means for ecosystem responses to nutrient availability is not trivial, especially in the context of fire and herbivory. However, it is clear that soil nutrients likely affect tree and grass growth and competition in savannas, which suggests that future changes in nutrient cycling, such as N deposition, may have important effects on savanna vegetation.

ADOPTION OF SORGHUM NATIONAL INTEGRATED SOLUTIONS TECHNICAL PACKAGE BY RAINFED FARMERS, GEZIRA, SUDAN

The effect of climate change on African agriculture represents a major challenge to continental agricultural development including food security, nutrition and management. In Sudan, the yield of rainfed crops is characterized by high variability in the yield due to the high variability in seasonal rainfall and does not exceed two sacs/feddan because the rainfed farmers were adopted low input rainfed agriculture as a risk management option which led to reduce in the yield per unit of land and water. The Federal Ministry of Agriculture has designed and financed a special programme for the traditional the rainfed sector of the country called Integrated Solutions Programme as the main adaptation strategy for the 2014/ 2020 growing seasons to diversify and increase production and productivity of crops cultivated in traditional rainfed areas in each State of the country such as sorghum, sesame, millet and sunflower. This programme was implemented by the Administration of Agricultural Extension and Technology Transfer in each State in collaboration with Agricultural Research Corporation (ARC) and the Agricultural Bank of Sudan. Field survey was used to collect data from 50 rainfed farmers participated in the programme and an equal number from non- participant farmers from the study area were selected (for comparison) using the simple random sampling technique. A close ended questionnaire was constructed and the personal interview technique was used to administer the questionnaire. The collected data were coded, fed to computer and statistically analyzed using (SPSS), discussed interpreted using descriptive statistics and chi-square test. The results showed that the participant farmers adopted the programme components. The majority of chi-square test results revealed no significant association between farmer`s adoption of the programme components and participation in the programme and also no significant association between farmer`s adoption of the programme components and the selected socio-economic characteristics of the respondent farmers. From this study, it can be concluded that the NISP are very effective agricultural extension policy that can be applied in the rainfed sector of the country, which will help rainfed farmers to increase their income through their participation in various activities of the programme. The study recommends that NISP should become the main national policy specially designed for the agricultural rainfed sector of the country, the needed agricultural inputs should be available at a reasonable price, the curriculum of NISP should be updated and developed regularly to solve the constraints that might face the programme, in-service training should be organized for agricultural extension officers on various aspects related to the rainfed sector, various means for conduction the programme should be available, Further agricultural extension research should be conducted

The Effect of ENSO on Seasonal Rainfall Using the Monte-Carlo Bootstrap Method in the Southern Part of Java, Indonesia

The Effect of ENSO on Seasonal Rainfall Using the Monte-Carlo Bootstrap Method in the Southern Part of Java, Indonesia

CHIRPS rainfall product application for analyzing rainfall concentration and seasonality in Johor river basin, Malaysia

It is crucial to carry out a spatiotemporal evaluation of rainfall concentration in the Johor river basin (JRB) given that erratic rainfall can lead to floods. The study utilized the CHIRPS rainfall dataset from 1983 to 2018 to determine rainfall concentration using the Concentration Index (CI). To further define the rainfall regime, the Seasonality Index (SI) and Precipitation Concentration Index (PCI) were examined. The Mann-Kendall (MK) test was utilized to examine the trend at a 95% level of significance. The results showed the better accuracy of SI than PCI in classifying the rainfall regime in the JRB, defined as “equable but with a definite wetter season” type. The CI values ranged from 0.61 to 0.72 and were typically high all over the basin, with the northwestern and western regions having the highest values. At 27 grid points on the eastern border of the upper and middle parts of the basin, CI has significantly increased as a result of an upsurge in rainfall concentration brought on by climate change. More than 67% and up to 83% of the yearly rainfall for all grid locations was accounted for by the North East monsoon (NEM), with the 25% wettest days caused by high-intensity rainfall events.

Influence mechanism of seasonal rainfall on hydrothermal changes of permafrost active layer in the central Qinghai-Tibet Plateau

Influence mechanism of seasonal rainfall on hydrothermal changes of permafrost active layer in the central Qinghai-Tibet Plateau

A comparative study of SPI, PCI, PCD, and RAI methods for estimating drought in the Palu River Basin, Indonesia

The Palu Watershed is vulnerable to extreme hydrological events, especially periods of heavy rains and prolonged dry seasons. This study aims to determine the drought index and the results of a comparison of the drought index between the Standardized Precipitation Index (SPI) and the Rainfall Anomaly Index (RAI), Rainfall Concentration Index (PCI), Rainfall Concentration Level (PCD), and Rainfall Concentration Period (PCP). The data used are monthly rainfall from Bora, Kalawara, Kulawi, Palolo, and Wuasa stations with observation periods from 1985 to 2021. The Pearson and Spearman correlation coefficients are used to determine the relationship between SPI and RAI, PCI, PCD, and PCP. RMSE and MAE are used to find out the absolute error in predictions. The results obtained show: PCI shows a uniform distribution of rainfall (76.57%) and moderately seasonal (32.43%) there is no distribution of seasonal and strongly seasonal rainfall, the dominant SPI is the normal category followed by mild and moderate drought, PCD and PCP show that rainfall is homogeneous and distributed throughout years and no rain is concentrated at any one time, Comparison of the relationship between SPI and RAI is very strong and significant compared to SPI versus PCI, SPI versus PCD and SPI versus PCP.

A new MIS 5 to MIS 2 speleothem record from Sandkraal Cave on the South African Cape south coast

AbstractWe present new stable oxygen and carbon isotope composite records (δ18O, δ13C) of speleothems from Sandkraal Cave 1 (SK1) on the South African south coast for the time interval between 104 and 18 ka (with a hiatus between 48 and 41 ka). Statistical comparisons using kernel-based correlation analyses and semblance analyses based on continuous wavelet transforms inform the relationships of the new speleothem records to other proxies and their changes through time. Between 105 and ~70 ka, changes of speleothem δ18O values at SK1 are likely related to rainfall seasonality. Variations of δ13C values are associated with changes of vegetation density, prior carbonate precipitation (PCP), CO2 degassing in the cave, and possibly variations of the abundance of C3 and C4 grasses in the vegetation. The relationships of δ18O with other proxies shift between ~70 and 48 ka (Marine Isotope Stages 4–3) so that both stable isotope records now reflect CO2 degassing, evaporation, and PCP. Similar relationships also continue after the hiatus for the deposition phase between 42 and 18 ka. Our findings support modeling results suggesting drier conditions in the study area when the Southern Hemisphere westerlies are shifted north and the paleo–Agulhas Plain is exposed.

Introducing Pour Points: Characteristics and Hydrological Significance of a Rainfall‐Concentrating Mechanism in a Water‐Limited Woodland Ecosystem

AbstractThe interception of rainfall by plant canopies alters the depth and spatial distribution of water arriving at the soil surface, and thus the location, volume, and depth of infiltration. Mechanisms like stemflow are known to concentrate rainfall and route it deep into the soil, yet other mechanisms of flow concentration are poorly understood. This study characterizes pour points, formed by the detachment of water flowing under a branch, using a combination of field observations in Western Australian banksia woodlands and rainfall simulation experiments on Banksia menziesii branches. We aim to establish the hydrological significance of pour points in a water‐limited woodland ecosystem, along with the features of the canopy structure and rainfall that influence pour point formation and fluxes. Pour points were common in the woodland and could be identified by visually inspecting trees. Throughfall depths at pour points were up to 15 times greater than rainfall and generally comparable to or greater than stemflow. Soil water content beneath pour points was greater than in adjacent controls, with 20%–30% of the seasonal rainfall volume infiltrated into the top 1 m of soil beneath pour points, compared to 5% in controls. Rainfall simulations showed that pour points amplified the spatial heterogeneity of throughfall, violating assumptions used to close the water balance. The simulation experiments demonstrated that pour point fluxes depend on the interaction of branch angle and foliation for a given branch architecture. Pour points can play a significant part in the water balance, depending on their density and rainfall concentration ability.

Spatiotemporal assessment of rainfall variability and its characteristics over Rapti River Basin, India

Abstract The determination of rainfall characteristics of a basin is obligatory for mitigation planning and adaptation. This study presents the spatiotemporal analysis of gridded precipitation to understand the variability and seasonality over the Rapti Basin. This basin is affected by frequent flooding; hence it becomes necessary to understand the variability of rainfall. To carry out this analysis, daily precipitation data is extracted for 22 grids for 30 years (1990–2020) of high resolution. Extreme rainfall indices are computed as per the threshold decided by the Indian Meteorological Department (IMD). To determine the trend of the rainfall, Mann Kendall (MK) test, Modified MK test and Innovative Trend Analysis was used and magnitude of trend was determined using slope. Trends of daily rainfall, annual, and seasonal rainfall were determined. Annual rainfall has shown significant decreasing trend over the basin. Monsoon season has a noticeable tendency, but other seasons have only seen small shifts. From all the rainfall indices, PRCPTOT and SDII showed a decreasing trend with Sen Slope of −2.56 and 3.00 respectively. While examining the variance in precipitation across the basin, this study will be helpful.

Toward a coordinated understanding of hydro-biogeochemical root functions in tropical forests for application in vegetation models.

Tropical forest root characteristics and resource acquisition strategies are underrepresented in vegetation and global models, hampering the prediction of forest-climate feedbacks for these carbon-rich ecosystems. Lowland tropical forests often have globally unique combinations of high taxonomic and functional biodiversity, rainfall seasonality, and strongly weathered infertile soils, giving rise to distinct patterns in root traits and functions compared with higher latitude ecosystems. We provide a roadmap for integrating recent advances in our understanding of tropical forest belowground function into vegetation models, focusing on water and nutrient acquisition. We offer comparisons of recent advances in empirical and model understanding of root characteristics that represent important functional processes in tropical forests. We focus on: (1) fine-root strategies for soil resource exploration, (2) coupling and trade-offs in fine-root water vs nutrient acquisition, and (3) aboveground-belowground linkages in plant resource acquisition and use. We suggest avenues for representing these extremely diverse plant communities in computationally manageable and ecologically meaningful groups in models for linked aboveground-belowground hydro-nutrient functions. Tropical forests are undergoing warming, shifting rainfall regimes, and exacerbation of soil nutrient scarcity caused by elevated atmospheric CO2. The accurate model representation of tropical forest functions is crucial for understanding the interactions of this biome with the climate.

Sensitivity of Rainfall Extremes to Unprecedented Indian Ocean Dipole Events

AbstractStrong positive Indian Ocean Dipole (pIOD) events like those in 1997 and 2019 caused significant flooding in East Africa. While future projections indicate an increase in pIOD events, limited historical data hinders a comprehensive understanding of these extremes, particularly for unprecedented events. To overcome this we utilize a large ensemble of seasonal reforecast simulations, which show that regional rainfall continues to increase with pIOD magnitude, with no apparent limit. In particular we find that extreme rain days are highly sensitive to the pIOD index and their seasonal frequency increases super‐linearly with higher pIOD magnitudes. It is vital that socio‐economic systems and infrastructure are able to handle not only the increasing frequency of events like 1997 and 2019 but also unprecedented seasons of extreme rainfall driven by as‐yet‐unseen pIOD events. Future studies should prioritize understanding the hydrological implications and population exposure to these unprecedented extremes in East Africa.